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• Conference paper
  Kogan F, Rosenberg J, McWalter EJ, Park D, Matzat S, Perkins K, Tran C, Taylor M, Sveinsson B, Newbould R, Monu U, Wang H, Bangerter N, Gold GEet al., 2014,

  Quantitative MRI of Osteoarthritis for Multicenter Trials: Standardization between Different Centers and Manufacturers

  , ISMRM 22nd Annual Meeting
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• Conference paper
  Mendoza MA, Villalpando R, Park DJ, Gardner D, Perkins K, Bangerter NKet al., 2014,

  Water Fat Separation with Multiple-Acquisition bSSFP

  , ISMRM 22nd Annual Meeting
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• Conference paper
  Taylor M, Wang H, Badal J, Perkins K, Park DJ, Kaggie J, Wisco J, Bangerter Net al., 2014,

  Relaxometry and Contrast Optimization for Laryngeal Imaging at 3 Tesla

  , ISMRM 22nd Annual Meeting
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• Conference paper
  Kaggie JD, Sapkota N, Jeong K, Shi X, Morrell GR, Bangerter N, Jeong E-Ket al., 2014,

  Synchronous 1 H and 23 Na dual-nuclear MRI on a clinical MRI system, equipped with a time-shared second transmit channel

  , ISMRM 22nd Annual Meeting
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• Conference paper
  Park DJ, Bangerter N, Morrell GR, 2014,

  Decoupled RF-pulse phase sensitive B1 mapping

  , ISMRM 22nd Annual Meeting
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• Journal article
  Scott AD, Ferreira P, Nielles-Vallespin S, McGill LA, Kilner PJ, Pennell DJ, Firmin Det al., 2014,

  Improved in-vivo cardiac DTI using optimal b-values

  , Journal of Cardiovascular Magnetic Resonance, Vol: 16, ISSN: 1097-6647
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  • Citations: 3
• Journal article
  Ali A, Hsu LY, Gulati A, Ismail T, Raphael CE, Vassiliou V, Chahal N, Krishnathansan K, Davendralingam N, Goncalves C, Wage R, Ferreira P, Baksi AJ, Gatehouse P, Firmin D, Pennell DJ, Kellman P, Arai AE, Prasad SKet al., 2014,

  The association between ECV and microcirculation perfusion abnormalities in non-ischemic dilated cardiomyopathy

  , Journal of Cardiovascular Magnetic Resonance, Vol: 16, ISSN: 1097-6647
  • Cite
  • Citations: 1
• Journal article
  Giannakidis A, Ferreira P, Scott AD, Nielles-Vallespin S, Babu-Narayan SV, Kilner PJ, Pennell DJ, Firmin Det al., 2014,

  Scanner-efficient diffusion tensor imaging of human cardiac microstructure using the fast composite splitting reconstruction algorithm

  , Journal of Cardiovascular Magnetic Resonance, Vol: 16, ISSN: 1097-6647
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  • Citations: 1
• Journal article
  Tunnicliffe EM, Scott AD, Ferreira P, Ariga R, McGill LA, Nielles-Vallespin S, Neubauer S, Pennell DJ, Robson MD, Firmin Det al., 2014,

  Inter-centre reproducibility of cardiac diffusion tensor measures

  , Journal of Cardiovascular Magnetic Resonance, Vol: 16, ISSN: 1097-6647
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• Conference paper
  Yang G, Raschke F, Barrick TR, Howe FAet al., 2014,

  Classification of brain tumour 1H MR spectra: Extracting features by metabolite quantification or nonlinear manifold learning?

  , IEEE The International Symposium on Biomedical Imaging (ISBI), Publisher: The Institute of Electrical and Electronics Engineers (IEEE), Pages: 1039-1042

  © 2014 IEEE. Proton magnetic resonance spectroscopy (1H MRS) provides non-invasive information on brain tumour biochemistry. Many studies have shown that 1H MRS can be used in an objective decision support system, which gives additional diagnosis and prognostic information to the data obtained using conventional radiological modalities. Fully automatic analyses of 1H MRS have been previously applied and can be separated into two types: (i) model dependent signal quantification followed by pattern recognition (PR), or (ii) model independent PR methods. However, there is not yet a consensus as to the best techniques of MRS post-processing or feature extraction to be used for optimum classification. In this study, we analysed the single-voxel MRS acquisitions of 74 patients with histologically diagnosed brain tumours. Our classification results show that the model independent nonlinear manifold learning method can produce superior results to those of using model dependent metabolite quantification.

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